Logistic Regression for Classification
This package provides logistic regression functions for both binary and multiclass classification problems.
This package is now a part of the PRML toolbox (http://www.mathworks.com/matlabcentral/fileexchange/55826-pattern-recognition-and-machine-learning-toolbox).
Cite As
Mo Chen (2021). Logistic Regression for Classification (https://www.mathworks.com/matlabcentral/fileexchange/55863-logistic-regression-for-classification), MATLAB Central File Exchange. Retrieved .
Comments and Ratings (10)
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Acknowledgements
Inspired by: Pattern Recognition and Machine Learning Toolbox, Kmeans Clustering
Inspired: One vs all classification using Logistic Regression for IRIS dataset
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Same error mentioned below, simple to fix (input t was not in correct orientation) - this should have been captured by input parsing at the start of the function. No NaN handling. No computation of standard errors, probabilities calculated do not match reality.
I'm having the same problem as Quoc Pham and Muhammad Tariq Sadiq. Any advice on this?
I got the same problem like Muhammad Tariq Sadiq, please advise!
Dear Sir, I am using following commands of your MATLAB codes
[model,llh]=logitBin(features,y);
plot(llh);
ytest = logitBinPred(model,features);
binPlot(model,features,ytest)
where features have length of 72*10 double and y have 72*1 double and representing class label.
When i execute the above code, I got following error
Error using -
Matrix dimensions must agree.
Error in logitBin (line 32)
g = X*(y-t)'+lambda.*w; % 4.96
Kindly suggest me how to remove it
t: 1 x n label (1~k)????
Great work! This saved me several hours, writing the code from Bishop myself.